-
有效检测烟雾,识别率高,机器学习cnn_evaluation_smoke-master
说明: 此代码简单易学,能有效检测烟雾,识别率高,机器学习。(This code is easy to learn, can effectively detect smoke, high recognition rate, machine learning.)
- 2020-07-07 23:08:56下载
- 积分:1
-
com.tencent.qb.plugin.arqbar9
说明: Subterranean homesick alien
- 2019-03-03 00:19:02下载
- 积分:1
-
Expert Python Programming, 2nd Edition
Become an ace Python programmer by learning best coding practices and advance-level concepts with Python 3.5
- 2020-06-23 00:00:03下载
- 积分:1
-
MACD
计算股票MACD技术指标的相关函数并作图。。。。(Stock Technical indicators MACD computing correlation functions and plotted. . . .)
- 2021-04-07 23:19:01下载
- 积分:1
-
Clustering
1) 使用凝聚型层次聚类算法(即最小生成树算法)对所有数据点进行聚类,最后聚成3类。相异度定义方法可选择single linkage、complete linkage、average linkage或者average group linkage中任意一种。
2) 使用C-Means算法对所有数据点进行聚类。C=3。
任务2(必做):
使用高斯混合模型(GMM)聚类算法对所有数据点进行聚类。C=3。并请给出得到的混合模型参数(包括比例??、均值??和协方差Σ)。
任务3(全做):
1) 参考数据文件第三列的类标签,使用聚类有效性评价的外部方法Normalized Mutual Information指标,分别计算任务1和任务2聚类结果的有效性。
2) 使用聚类有效性评价的内部方法Xie-Beni指标,分别计算任务1和任务2聚类结果的有效性。(The main results are as follows: 1) the condensed hierarchical clustering algorithm (that is, the minimum spanning tree algorithm) is used to cluster all the data points, and finally it is grouped into three categories. Any of the single linkage,complete linkage,average linkage or average group linkage methods can be selected for the definition of dissimilarity. 2) using C-Means algorithm to cluster all data points. C = 3.)
- 2019-05-16 21:54:22下载
- 积分:1
-
pyautocad-master
说明: pyautocad from github
- 2019-10-07 20:12:11下载
- 积分:1
-
attributes
CUB_鸟类数据标注,每张图312特征,共计200分类(class_attribute_labels_continuous)
- 2020-06-22 18:40:01下载
- 积分:1
-
python
numpy库的使用说明,方便开发人工智能、神经网络相关的算法。(the Instructions of numpy)
- 2018-07-12 19:18:14下载
- 积分:1
-
Function for Bayesian and euclidean, z=mahalanobis_classifier(m,S,X).This function outputs the Mahal
- 2023-02-13 04:25:03下载
- 积分:1
-
LBM-2维扩散
采用格子玻尔兹曼方法解决2维扩散问题的Python代码
- 2022-07-07 04:45:51下载
- 积分:1